One obstacle to industrial technology education is that the difficulties or problems students encounter during experiments are not easy to detect. Students are often unaware of their flaws, and some will not notify the teacher of these flaws even if they are aware of them. Consequently, many opportunities to rectify these flaws and improve teaching methods are lost, and students who are falling behind are deprived of instant guidance and cannot catch up. Therefore, this paper aims to develop a web-based self-reflective learning system to enhance students' learning of industrial technology. This study applied sensor network technology to develop a web-based self-reflective learning system based on a self-reflective learning approach. The system was integrated into a micro-fabrication technology course for empirical study. Subsequently, the influence of the web-based self-reflective learning system on students' learning performance and technical skills was investigated. Analysis of the data obtained from learning cognition, skill assessment, and learning satisfaction following education indicated that the web-based self-reflective learning system could effectively improve the learning performance of students falling behind, thereby allowing these students to catch up in their cognitive and skill achievements by the end of the semester. (Contains 4 figures and 4 tables.)